Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/89200
Title: Modelling energy demand in response to weather conditions for the Maltese Islands
Authors: Mallia, John (2005)
Keywords: Power resources -- Malta
Weather
Natural resources -- Malta
Issue Date: 2005
Citation: Mallia, J. (2005). Modelling energy demand in response to weather conditions for the Maltese Islands (Bachelor's dissertation).
Abstract: Energy production in the Maltese Islands has been increasing in response to an evergrowing consumption. Several factors have contributed to this scenario. Changes in lifestyles, affluence, as well as the introduction of innovative ideas and goods in the market have led to an increase in demand for energy. These are factors which contribute to an increase in energy demand in the long-term. However other factors, such as changing weather conditions, may contribute to more sudden fluctuations in energy demand. These fluctuations, when not predicted, can lead to sudden surges in energy demand and, if the generation and distribution systems cannot respond promptly, power cuts are very likely to occur. This dissertation tries to investigate the relationship between energy demand on a national scale, and both seasonal and daily weather fluctuations. The data used in this work was obtained from the National Meteorological Office at the Malta International Airport, and from Enemalta Corporation, the national electricity provider. Meteorological data primarily consists of temperature and humidity data, while cloud cover, wind and sunshine data being also considered. Data from Enemalta Corporation include figures for energy demand during the night, day and evening periods. This study presents a set of four hypotheses related to the effect which weather variables have on energy demand, and then proceeds to test them. Data were inputted in the SPSS statistical software and analysed through the construction of statistical models with the aim of predicting energy demand. This is performed by using weather variables and other time variables which are significant for the prediction of energy demand formulae. The study derives its conclusions from the analysis of the models and the prediction formulae, whose coefficients reflect the effect of weather on energy demand, and the way people in a society react to weather conditions.
Description: B.A.(HONS)GEOGRAPHY
URI: https://www.um.edu.mt/library/oar/handle/123456789/89200
Appears in Collections:Dissertations - FacArt - 1999-2010
Dissertations - FacArtGeo - 1983-2008

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